It has now become common place for individuals and businesses to list items they want to sell (or information they want others to have) in a database accessible to users. Some of the databases contain consumer goods and services, such as cars, books, maps, electronics, medicine, job listings, newspapers, etc. Other databases contain information, such as definitions, specifications, names and addresses and the like. These databases are organized, usually by a sponsor, so that anyone of the general public can access the database and enter keywords or otherwise search for a desired item or piece of information. Other databases require some form of pre-membership, either for a cost or free, where passwords or other security devices limit access to only those with an affinity to a particular database.
One thing these databases have in common is that they are separate entities that do not know or otherwise “understand” other databases that may (or may not) contain the same or similar items. Typically, a user attempting to obtain information must affirmatively access a database to retrieve the information. This operation is called “pulling” the information from the database. A fundamental operating parameter for pulling-type systems is that the user must: a) manually perform a search of a select database (or set of databases) every time a search is requested; b) sort through the information returned from every request—often performing further sub-searches based on unique descriptors; c) find the stored data in the place searched; and, d) if successful; then e) then access the data. This operation is repeated using other known databases until the correct information is pulled or until the user gives up. This operation is especially frustrating for users who search unsuccessfully but must find the proper information, or for those users that search regularly but are often unsuccessful (and therefore must repeat the search process until successful). This requires the user to spend time searching and thus is not practical for many applications and especially not useful when the user is otherwise occupied.
Search engines attempt to search all “net” connected databases, but typically fail due to numerous reasons, including: a) items may be coded into the database in such a manner as to make it difficult for search engines to navigate; b) items may be too deep within the database hierarchy; c) items in the database may not have sufficient descriptors to be caught by the search engine; and d) the search engine user may be using an unfamiliar or incorrect descriptor vs. the descriptor(s) used by the database originator and/or search engine.
A further drawback that exists with present systems is that they are primarily stand-alone and thus the data from one database or source does not easily integrate with data from another source.
Other problems exist when a user is attempting to input data. Any such inputted data is treated as an independent event. Thus, when a user inputs data pertaining to a specific item the user must either fill out fields in a preexisting form or must independently decide what information to include. Again, this is time consuming and in some situations leads to less than all of the desired (descriptive) information being supplied or supplied in a manner which promotes inefficient use of the material.